976 resultados para framework species
Resumo:
Four morphologically cryptic species of the Bactrocera dorsalis fruit fly complex (B. dorsalis s.s., B. papayae, B. carambolae and B. philippinensis) are serious agricultural pests. As they are difficult to diagnose using traditional taxonomic techniques, we examined the potential for geometric morphometric analysis of wing size and shape to discriminate between them. Fifteen wing landmarks generated size and shape data for 245 specimens for subsequent comparisons among three geographically distinct samples of each species. Intraspecific wing size was significantly different within samples of B. carambolae and B. dorsalis s.s. but not within samples of B. papayae or B. philippinensis. Although B. papayae had the smallest wings (average centroid size=6.002 mm±0.061 SE) and B. dorsalis s.s. the largest (6.349 mm±0.066 SE), interspecific wing size comparisons were generally non-informative and incapable of discriminating species. Contrary to the wing size data, canonical variate analysis based on wing shape data discriminated all species with a relatively high degree of accuracy; individuals were correctly reassigned to their respective species on average 93.27% of the time. A single sample group of B. carambolae from locality 'TN Malaysia' was the only sample to be considerably different from its conspecific groups with regards to both wing size and wing shape. This sample was subsequently deemed to have been originally misidentified and likely represents an undescribed species. We demonstrate that geometric morphometric techniques analysing wing shape represent a promising approach for discriminating between morphologically cryptic taxa of the B. dorsalis species complex.
Resumo:
1 Diachasmimorpha krausii is a braconid parasitoid of larval tephritid fruit flies, which feed cryptically within host fruit. At the ovipositor probing stage, the wasp cannot discriminate between hosts that are physiologically suitable or unsuitable for offspring development and must use other cues to locate suitable hosts. 2 To identify the cues used by the parasitoid to find suitable hosts, we offered, to free flying wasps, different combinations of three fruit fly species (Bactrocera tryoni, Bactrocera cacuminata, Bactrocera cucumis), different life stages of those flies (adults and larvae) and different host plants (Solanum lycopersicon, Solanum mauritianum, Cucurbita pepo). In the laboratory, the wasp will readily oviposit into larvae of all three flies but successfully develops only in B. tryoni. Bactrocera tryoni commonly infests S. lycopersicon (tomato), rarely S. mauritianum (wild tobacco) but never C. pepo (zucchini). The latter two plant species are common hosts for B. cacuminata and B. cucumis, respectively. 3 The parasitoid showed little or no response to uninfested plants of any of the test species. The presence of adult B. tryoni, however, increased parasitoid residency time on uninfested tomato. 4 When the three fruit types were all infested with larvae, parasitoid response was strongest to tomato, regardless of whether the larvae were physiologically suitable or unsuitable for offspring development. By contrast, zucchini was rarely visited by the wasp, even when infested with B. tryoni larvae. 5 Wild tobacco was infrequently visited when infested with B. cacuminata larvae but was more frequently visited, with greater parasitoid residency time and probing, when adult flies (either B. cacuminata or B. tryoni) were also present. 6 We conclude that herbivore-induced, nonspecific host fruit wound volatiles were the major cue used by foraging D. krausii. Although positive orientation to infested host plants is well known from previous studies on opiine braconids, the failure of the wasp to orientate to some plants even when infested with physiologically suitable larvae, and the secondary role played by adult fruit flies in wasp host searching, are newly-identified mechanisms that may aid parasitoid host location in environments where both physiologically suitable and unsuitable hosts occur.
Resumo:
In this study, we investigate the relationship between tree species diversity and production in 18 mixed-species plantations established under the Rainforestation Farming system in Leyte province, the Philippines. The aim was to quantify productivity in the mixed-species plantations in comparison to the monocultures, and identify key drivers of productivity including environmental conditions, stand structural characteristics and surrogate measures of biodiversity, i.e. species richness, Shannon’s diversity index and functional groups. We found that monocultures had a much higher productivity than mixtures of the same and other species. In the mixtures, biodiversity and productivity did not have a simple relationship. Instead the proportion of exotic and native species, and the proportion of fast-growing species had a marginally significant positive effect on stand productivity, but no significant relationship was found with species richness or Shannon’s diversity. Instead stand structural characteristics such as density and age were the strongest drivers of increased productivity. Production levels within the mixed-species plantations varied significantly between sites. Overall, we found that the productivity of mixed species plantations was driven more by the characteristics of species present and stand structural characteristics then by simply the number and abundance of species, which suggests management practices are key for balancing multiple objectives to meet sustainable development needs.
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Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. Synthesis and applications.In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.
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Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.
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Flexibility is a key driver of any successful design, specifically in highly unpredictable environment such as airport terminal. Ever growing aviation industry requires airport terminals to be planned and constructed in such a way that will allow flexibility for future design, alteration and redevelopment. The concept of flexibility in terminal design is a relatively new initiative, where existing rules or guidelines are not adequate to assist designers. A shift towards flexible design concept would allow terminal buildings to be designed to accommodate future changes and to make passengers’ journey as simple, timely and hassle free as possible. Currently available research indicates that a theoretical framework on flexible design approach for airport terminals would facilitate the future design process. The generic principles of flexibility are investigated in the current research to incorporate flexible design approaches within the process of an airport terminal design. A conceptual framework is proposed herein, which is expected to ascertain flexibility to current passenger terminal facilities within their corresponding locations as well as in future design and expansion.
Resumo:
Key establishment is a crucial primitive for building secure channels in a multi-party setting. Without quantum mechanics, key establishment can only be done under the assumption that some computational problem is hard. Since digital communication can be easily eavesdropped and recorded, it is important to consider the secrecy of information anticipating future algorithmic and computational discoveries which could break the secrecy of past keys, violating the secrecy of the confidential channel. Quantum key distribution (QKD) can be used generate secret keys that are secure against any future algorithmic or computational improvements. QKD protocols still require authentication of classical communication, although existing security proofs of QKD typically assume idealized authentication. It is generally considered folklore that QKD when used with computationally secure authentication is still secure against an unbounded adversary, provided the adversary did not break the authentication during the run of the protocol. We describe a security model for quantum key distribution extending classical authenticated key exchange (AKE) security models. Using our model, we characterize the long-term security of the BB84 QKD protocol with computationally secure authentication against an eventually unbounded adversary. By basing our model on traditional AKE models, we can more readily compare the relative merits of various forms of QKD and existing classical AKE protocols. This comparison illustrates in which types of adversarial environments different quantum and classical key agreement protocols can be secure.
Resumo:
Positive user experience (UX) has become a key factor in designing interactive products. It acts as a differentiator which can determine a product’s success on the mature market. However, current UX frameworks and methods do not fully support the early stages of product design and development. During these phases, assessment of UX is challenging as no actual user-product interaction can be tested. This qualitative study investigated anticipated user experience (AUX) to address this problem. Using the co-discovery method, participants were asked to imagine a desired product, anticipate experiences with it, and discuss their views with another participant. Fourteen sub-categories emerged from the data, and relationships among them were defined through co-occurrence analysis. These data formed the basis of the AUX framework which consists of two networks which elucidate 1) how users imagine a desired product and 2) how they anticipate positive experiences with that product. Through this AUX framework, important factors in the process of imagining future products and experiences were learnt, including the way in which these factors interrelate. Focusing on and exploring each component of the two networks in the framework will allow designers to obtain a deeper understanding of the required pragmatic and hedonic qualities of product, intended uses of product, user characteristics, potential contexts of experience, and anticipated emotions embedded within the experience. This understanding, in turn, will help designers to better foresee users’ underlying needs and to focus on the most important aspects of their positive experience. Therefore, the use of the AUX framework in the early stages of product development will contribute to the design for pleasurable UX.
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This chapter opens with a description of the empirical realities that shape and have shaped many women's choice to sell sex – realities which have remained constant for some time now. It provides two frameworks for understanding, first, the shifting discourses that currently constitute prostitution, and second, prostitution policies. The chapter also provides a narrative framework in which recent policy changes can be placed.
Resumo:
The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.